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Practice Midterm with Solution

Essay by   •  March 13, 2017  •  Exam  •  1,458 Words (6 Pages)  •  1,063 Views

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Practice Midterm

Question 1: (1x10=10 points) circle the most appropriate choice

  1. Operations management is concerned with
  1. the design of a firm’s productive systems.
  2. the operation of a firm’s productive systems.
  3. the improvement of a firm’s productive systems.
  4. all of the above.

  1. (i) Forecasting customer demand is rarely a key to providing good quality service.  (ii) The ratio of a firm’s monthly output to the number of labor hours used in the same month would be a measure of labor productivity
  1. (i) true (ii) false        b. (i) false (ii) true                c. both true                d. both false
  1. A gradual, long-term up or down movement of demand is referred to as a
  1. Seasonality                b. cyclicality                        c. trend                 d. correlation
  1. Exponential smoothing method is designed for
  1. Stationary series        b. Seasonality                c. Trend                 d. All of the a,b,c
  1. The exponential smoothing model produces a naïve forecast when the smoothing constant, α, is equal to 
  1. 0.00                        b. 1.00                        c. 0.50                d. 2.00

  1. The economic order quantity (EOQ) model determines the optimal order size that minimizes  
  1. annual carrying cost
  2. annual order cost
  3. total annual inventory cost
  4. annual purchase cost
  1. (i) Inventory management is concerned with how much to order and when to order.  (ii) The three basic costs associated with inventory are holding costs, ordering costs and shortage costs.
  1. (i) True (ii) False
  2. (i) False (ii) True
  3. Both true
  4. Both false
  1. (i) The production quantity model, a variation of the basic EOQ model, assumes non-instantaneous replenishment.(ii) With the economic order quantity (EOQ) model, increasing the order quantity reduces inventory carrying cost.
  1. (i) True (ii) False        b. (i) False (ii) True                c. Both true         d. Both false
  1. A continuous inventory system is also known as a
  1. fixed time period system
  2. fixed order quantity system
  3. fixed lead time system
  4. fixed amount system

1.10 A company may purchase larger amounts of inventory for all the following reasons except

  1. to take advantage of quantity discounts.
  2. as a hedge against future price increases.
  3. to obtain lower prices purchasing in volume.
  4. to reduce inventory carrying costs.

Question 2: (10 points)

Consider the following demand data:

Period

1

2

3

4

Demand

500

590

710

780

  1. (2 points) Compute a 2-month moving average forecasts for months 3 through 5.

[pic 1],[pic 2],[pic 3]

  1. (2 points) Compute a weighted 2-month moving average forecasts for months 3 through 5. Assign weights of 0.70 and 0.30 to the more recent and more distant data respectively.

[pic 4],[pic 5],[pic 6]

  1. (2 points) Compare the two forecasting methods using MSE. Which method is more accurate?

2-month SMA: MSE =  (also accepted 44,135)[pic 7]

2-month WMA(more accurate): MSE =  (also accepted 32,845) [pic 8]

  1. (2 points) Compute an exponentially smoothed forecast for period 3 using an  value of 0.25. Assume that the first period’s forecast is the same as its demand.[pic 9]

[pic 10]

  1. (2 points) Compute an adjusted exponentially smoothed forecast for period 3 . Use the second period’s forecast from part d. Assume that the second period’s trend is zero.[pic 11]

[pic 12]

[pic 13]

Question 3: (10 points)

Consider the following demand data for outdoor recreational clothing:

2012

2013

2014

Total

Winter

130

135

145

410

Spring

205

210

230

645

Summer

115

145

160

420

Fall

360

370

430

1160

Total

810

860

965

2635

Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for 2015 (using a linear trend line forecast estimate for orders in 2015).

Seasonality factor:[pic 14]

Winter: 410/2635 = 0.1556

Spring: 645/2635 = 0.2448        

Summer: 420/2635 = 0.1594        

Fall: 1160/2635 = 0.4402                

Forecast Annual Sales, 2015

[pic 15]

[pic 16]

[pic 17]

[pic 18]

1

810

810

1

2

860

1720

4

3

965

2895

9

Sum

6

2635

5425

14

Average

2

2635/3=878.33

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